class_docstr: The LogisticRidgeRegression class is used to fit logistic ridge regression models against one or more labels optimized over a
  provided list of ridge alpha parameters. The optimal ridge alpha value is chosen for each label by minimizing the
  average out of fold log_loss scores.
docstr: Fits a logistic ridge regression model, then transforms the matrix using the model.
  
  Args:
      response : String specifying the desired output.  Can be 'linear' to specify the direct output of the linear
          WGR model (default) or 'sigmoid' to specify predicted label probabilities.
  
  Returns:
      Pandas DataFrame containing prediction y_hat values. The shape and order match labeldf such that the
      rows are indexed by sample ID and the columns by label. The column types are float64.
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code: def fit_transform(self, response: str = "linear") -> pd.DataFrame:
      """
      Fits a logistic ridge regression model, then transforms the matrix using the model.
  
      Args:
          response : String specifying the desired output.  Can be 'linear' to specify the direct output of the linear
              WGR model (default) or 'sigmoid' to specify predicted label probabilities.
  
      Returns:
          Pandas DataFrame containing prediction y_hat values. The shape and order match labeldf such that the
          rows are indexed by sample ID and the columns by label. The column types are float64.
      """
      self.fit()
      return self.transform(response)
  
imports: from .logistic_udfs import *
  from .ridge_reduction import RidgeReduction
  from .model_functions import _prepare_labels_and_warn, _prepare_covariates, _check_model, _check_cv, _is_binary
  from nptyping import Float, NDArray
  import pandas
  from pyspark.sql import DataFrame
  from pyspark.sql.functions import pandas_udf, PandasUDFType
  import pyspark.sql.functions
  from typeguard import typechecked
  from typing import Any, Dict, List
  import warnings
  from glow.logging import record_hls_event
label_desc: Use image node_id 16 for calling the LogisticRidgeRegression obj's underlying member method code with example usage: obj.fit_transform(response) and returns: self